Background

Notes and format last updated May 7, 2020

Starting on the May 7th update, the NY Times began including probable covid cases/deaths along with confirmed. This mostly affects death counts – for certain geographies that include probable COVID deaths in addition to confirmed, these are now added to the totals. For the time being, they were all added to the May 6th totals, causing a big spike at the U.S. level. Over time, NY Times will revise their historical counts and distribute these added deaths when they actually occurred, so the spike should fade.

Growth rates

Heat maps

  • The two heat maps below compare how quickly total cases or deaths have grown at various times in our respective geopgraphies.
  • The first plot compares growth rate for total cases; the second, growth rate for total deaths.
  • The metric used is doubling time, by which I mean how quickly total cases or deaths are doubling.
  • The plots track that doubling time at each date for our geographies. Darker colors reflect shorter doubling times, and thus periods of faster growth.
    • You can use the plots to track each geography over time and to compare the geographies to one another.
    • You can also compare the cases and death charts, to see how faster periods of death growth follow faster periods of case growth.

Case growth rates

  • This section charts the growth rate of both total and new cases for each of our respective geographies. Each geography has its own chart, and then that chart will have a trendline for total cases and new cases.
    • There are only plots for the U.S. and states because the numbers for the counties are too small to generate worthwhile trendlines in this section.
  • Note that we’re charting growth rate and not a count of cases, so don’t think of these as the standard “curve” that we hear about in the news and that we want to flatten. Instead, these growth rate charts help track more precisely what we can only estimate when we see those other curves. For these growth rate charts, if the line is above zero, the metric we are tracking (total or new cases) is continuing to grow. If the growth rate line is going up, it’s growing more quickly each day; if it’s going down but still above zero, it’s growing less quickly (but still growing). Only when the growth rate lines go below zero has the metric stopped growing.
  • Each of these two lines uses rolling windows to calculate a growth rate for that particular metric. I do the calculation differently for each to smooth out some of the large day-to-day discrepancies in new case reporting at the state level.
    • For total cases, the trendlines are a rolling 3-day average of daily growth rates in total cases. We want to see these decline (and almost all are), but they can’t go below zero. This is because we’re tracking growth rate and a growth rate line below zero would mean total cases have gone down, which can’t happen. They can only grow less quickly, which means we want to see the total case line get as close to zero as possible.
    • For new cases, the trendlines show a rolling 3-day average of daily growth rate in the rolling 7-day average of new cases. Including two rolling periods in this average helps smooth out crazy spikes at the state level that result from large day-to-day changes. Unlike the lines for total cases, we want to watch for the lines for new cases to get consistently below zero and stay there. That means that we are consistently seeing fewer new cases on a daily basis.

U.S.

Our states

Death growth rates

  • This section charts the growth rate of both total and new deaths for each of our respective geographies. Each geography has its own chart, and then that chart will have a trendline for total deaths and new deaths.
    • There are only plots for the U.S. and states because the numbers for the counties are too small to generate worthwhile trendlines in this section.
  • Note that we’re charting growth rate and not a count of deaths, so don’t think of these as the standard “curve” that we hear about in the news and that we want to flatten. Instead, these growth rate charts help track more precisely what we can only estimate when we see those other curves. For these growth rate charts, if the line is above zero, the metric we are tracking (total or new deaths) is continuing to grow. If the growth rate line is going up, it’s growing more quickly each day; if it’s going down but still above zero, it’s growing less quickly (but still growing). Only when the growth rate lines go below zero has the metric stopped growing.
  • Each of these two lines uses rolling windows to calculate a growth rate for that particular metric. I do the calculation differently for each to smooth out some of the large day-to-day discrepancies in new death reporting at the state level.
    • For total deaths, the trendlines are a rolling 3-day average of daily growth rates in total deaths. We want to see these decline (and almost all are), but they can’t go below zero. This is because we’re tracking growth rate and a growth rate line below zero would mean total deaths have gone down, which can’t happen. They can only grow less quickly, which means we want to see the total death line get as close to zero as possible.
    • For new deaths, the trendlines show a rolling 3-day average of daily growth rate in the rolling 7-day average of new deaths. Including two rolling periods in this average helps smooth out crazy spikes at the state level that result from large day-to-day changes. Unlike the lines for total deaths, we want to watch for the lines for new deaths to get consistently below zero and stay there. That means that we are consistently seeing fewer new deaths on a daily basis.

U.S.

Our states

By population rankings

This section tracks metrics for states and counties normalized for population (number of cases or deaths per million residents), and then compares these figures both for our geographies and the country overall.

States

  • This section shows tables ranking all 50 states for per populations rates of total cases, new cases, total deaths, and new deaths.
  • For each metric, in addition to the tables, the trends for the top states are plotted over time.
    • We only plot the top ten states for each metric so that the plots aren’t too crowded. But you can view the full 50-state rankings in the tables.

Total confirmed cases

Table of total confirmed cases per million residents (all 50 states)
Ranking State Cases Per Million
1 North Dakota 134,149
2 South Dakota 131,829
3 Rhode Island 127,709
4 Utah 119,564
5 Tennessee 115,890
6 Arizona 115,128
7 Iowa 110,456
8 Oklahoma 110,312
9 Arkansas 109,188
10 Wisconsin 108,602
11 Nebraska 107,494
12 South Carolina 105,901
13 Alabama 104,654
14 Kansas 104,096
15 Mississippi 102,125
16 Indiana 101,642
17 Idaho 100,169
18 New Jersey 99,286
19 Nevada 98,114
20 Illinois 97,335
21 Montana 97,270
22 Georgia 96,693
23 Wyoming 96,620
24 Texas 95,598
25 Kentucky 95,576
26 Delaware 95,544
27 Louisiana 95,211
28 Missouri 94,764
29 Florida 94,396
30 New York 93,741
31 California 92,459
32 New Mexico 90,847
33 Minnesota 90,515
34 Massachusetts 90,275
35 North Carolina 86,657
36 Ohio 86,077
37 Connecticut 85,129
38 Alaska 84,147
39 Colorado 79,359
40 Pennsylvania 78,542
41 West Virginia 77,700
42 Virginia 71,496
43 Michigan 71,313
44 Maryland 66,852
45 District of Columbia 61,876
46 New Hampshire 60,335
47 Washington 47,446
48 Puerto Rico 43,473
49 Oregon 38,617
50 Maine 36,593
51 Vermont 29,191
52 Hawaii 20,566

New confirmed cases

Table of new cases per million residents: rolling 3-day average (all 50 states)
Ranking State New Cases Per Million
1 New York 611
2 Michigan 513
3 New Jersey 481
4 Rhode Island 393
5 Connecticut 359
6 New Hampshire 315
7 Pennsylvania 309
8 Massachusetts 307
9 Florida 251
10 South Dakota 245
11 Iowa 240
12 Alaska 238
13 Minnesota 238
14 Colorado 229
15 Montana 228
16 North Dakota 217
17 West Virginia 213
18 Delaware 208
19 Tennessee 203
20 Idaho 201
21 Vermont 200
22 South Carolina 197
23 Maryland 180
24 Illinois 179
25 North Carolina 176
26 Kentucky 170
27 Georgia 167
28 Virginia 167
29 Texas 156
30 Ohio 141
31 Missouri 140
32 Nebraska 140
33 District of Columbia 135
34 Maine 135
35 Wisconsin 133
36 Indiana 127
37 Utah 125
38 Mississippi 113
39 Washington 112
40 Louisiana 111
41 Wyoming 109
42 New Mexico 95
43 Alabama 92
44 Nevada 90
45 Arkansas 88
46 Oklahoma 88
47 Oregon 85
48 Kansas 76
49 California 65
50 Arizona 57
51 Puerto Rico 50
52 Hawaii 48

Total deaths

Table of total deaths per million residents (all 50 states)
Ranking State Deaths Per Million
1 New Jersey 2,739
2 New York 2,534
3 Massachusetts 2,467
4 Rhode Island 2,460
5 Mississippi 2,347
6 Arizona 2,318
7 Connecticut 2,205
8 South Dakota 2,178
9 Louisiana 2,166
10 Alabama 2,142
11 North Dakota 1,964
12 Pennsylvania 1,950
13 Indiana 1,928
14 New Mexico 1,868
15 Illinois 1,849
16 Arkansas 1,846
17 Iowa 1,809
18 South Carolina 1,764
19 Georgia 1,712
20 Tennessee 1,712
21 Michigan 1,701
22 Nevada 1,693
23 Kansas 1,675
24 Texas 1,655
25 Delaware 1,577
26 Ohio 1,572
27 Florida 1,534
28 District of Columbia 1,492
29 California 1,477
30 West Virginia 1,464
31 Missouri 1,450
32 Maryland 1,359
33 Kentucky 1,343
34 Montana 1,342
35 Wisconsin 1,248
36 Oklahoma 1,225
37 Minnesota 1,222
38 Wyoming 1,200
39 Virginia 1,188
40 Nebraska 1,178
41 North Carolina 1,146
42 Idaho 1,095
43 Colorado 1,069
44 New Hampshire 903
45 Washington 694
46 Puerto Rico 659
47 Utah 651
48 Oregon 564
49 Maine 543
50 Alaska 408
51 Vermont 357
52 Hawaii 321

New deaths

Table of new deaths per million residents: rolling 3-day average (all 50 states)
Ranking State New Deaths Per Million
1 Kentucky 11
2 Montana 6
3 Nebraska 6
4 Arizona 5
5 California 5
6 Georgia 5
7 Massachusetts 5
8 New Jersey 5
9 New York 5
10 North Carolina 5
11 Oklahoma 5
12 Alabama 4
13 Missouri 4
14 Nevada 4
15 Tennessee 4
16 Texas 4
17 Iowa 3
18 Kansas 3
19 Louisiana 3
20 Michigan 3
21 Mississippi 3
22 New Mexico 3
23 Pennsylvania 3
24 South Carolina 3
25 Arkansas 2
26 Florida 2
27 Minnesota 2
28 New Hampshire 2
29 North Dakota 2
30 Utah 2
31 Vermont 2
32 Washington 2
33 West Virginia 2
34 Alaska 1
35 Connecticut 1
36 Delaware 1
37 District of Columbia 1
38 Idaho 1
39 Illinois 1
40 Indiana 1
41 Maryland 1
42 Ohio 1
43 South Dakota 1
44 Wisconsin 1
45 Wyoming 1
46 Colorado 0
47 Hawaii 0
48 Maine 0
49 Oregon 0
50 Puerto Rico 0
51 Rhode Island 0
52 Virginia 0

Counties

  • This section focuses on the county level. It shows tables with our counties ranked by percentile of U.S. counties for per population rates of total cases and total deaths.
    • Each table also shows the top five counties in the country in addition to our counties, for added perspecive.
  • In addition to the tables, our counties’ percentile for both total cases and total deaths are plotted over time.

Confirmed cases

Table showing total cases per million and percentile for all US counties. Includes our counties and the top 5 in the US for perspective.
County State Cases Per Million Raw Ranking Percentile
Crowley Colorado 350,767 1 99
Chattahoochee Georgia 314,477 2 99
Bent Colorado 266,093 3 99
Lincoln Arkansas 243,781 4 99
Dewey South Dakota 243,551 5 99
Davidson Tennessee 134,821 207 93
Richland South Carolina 104,373 1042 66
York South Carolina 100,655 1215 61
Orange California 83,558 2007 36
Pierce Washington 45,877 2905 7

Our county percentiles over time

Deaths

Table showing total deaths per million and percentile for all US counties. Includes our counties and the top 5 in the US for perspective.
County State Deaths Per Million Raw Ranking Percentile
Gove Kansas 8,346 1 99
Jerauld South Dakota 7,948 2 99
Galax city Virginia 7,878 3 99
Foard Texas 7,792 4 99
Emporia city Virginia 7,669 5 99
Orange California 1,469 1782 43
Davidson Tennessee 1,279 2008 36
York South Carolina 1,271 2022 35
Richland South Carolina 1,260 2035 35
Pierce Washington 666 2726 13

Our county percentiles over time

Raw counts

Total confirmed cases

U.S.

Our states

Our counties

New confirmed cases

U.S.

Our states

Our counties

Total deaths

U.S.

Our states

Our counties

New deaths

U.S.

Our states

Our counties

Stay-at-home comparisons